ArticleEuropean heart journal2025
Artificial intelligence applied to electrocardiogram to rule out acute myocardial infarction: the ROMIAE multicentre study.
Article in European heart journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
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Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it.
- "First, do no harm" in the digital era: examining the practicality of the European Health Data Space proposal and ethical implications of artificial intelligence: A systematic literature review.BMC medical ethics · 2026Pooled it
- AI-Enabled Electrocardiogram for Rule-Out of NSTEMI Across Clinically Challenging Presentations.JACC. Advances · 2026Article
- Artificial intelligence in emergency medicine: from algorithmic performance to real-world clinical integration - understanding the implementation gap.International journal of emergency medicine · 2026Review
- Artificial intelligence-based ECG as a triage tool for acute myocardial infarction: a diagnostic systematic review and meta-analysis.European heart journal. Digital health · 2026Review
- Review
- Artificial Intelligence for the Detection of Hypertrophic Cardiomyopathy From Standard Electrocardiogram.JACC. Advances · 2026Article
- Sex-Consistent Performance of an AI-Enabled ECG for Acute Myocardial Infarction: The ROMIAE Study.JACC. Advances · 2026Article
- Artificial Intelligence-Enabled ECG for Elevated E/e' on Echocardiography: Hemodynamic Relevance and Prognostic Value.Journal of the American Heart Association · 2026Article
- External validation of ECG artificial intelligence for emergency and cardiac assessment across a large-scale U.S. healthcare system.NPJ digital medicine · 2026Article
- Artificial intelligence across the cardiovascular diagnostic pathway: a case-based narrative review.Cardiovascular diagnosis and therapy · 2026Review
- Artificial intelligence-enhanced electrocardiography for acute myocardial infarction detection: a systematic review.Cardiovascular diagnosis and therapy · 2026Review
- Pilot Study Comparing Emergency Physician and Artificial Intelligence-supported Interpretations of Electrocardiograms.The western journal of emergency medicine · 2026Article
- ECG trained artificial intelligence for the detection of patients with inducible myocardial ischemia.European heart journal. Digital health · 2026Article
- Silence of the Electrocardiogram: A Case Series With Occluded Coronaries and Normal Electrocardiograms.Journal of medical cases · 2026Article
- A practical ECG-based model for early identification of acute heart failure following acute myocardial infarction.Scientific reports · 2026Article
- Diagnostic challenges in acute coronary syndrome: reconciling the STEMI-NSTEMI and OMI-NOMI paradigms.BMC cardiovascular disorders · 2026Article
- Association of neutrophil-to-prognostic nutritional index ratio with long-term mortality in acute myocardial infarction from Chinese and US cohorts.Frontiers in nutrition · 2026Article
- Artificial intelligence-enabled electrocardiography from scientific research to clinical application.EMBO molecular medicine · 2026Review
- State of clinical AI in 2026.BMJ digital health & AI · 2026Review
- Artificial intelligence to improve patient care in emergency medicine: a workflow-based analysis.Internal and emergency medicine · 2026Article
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22 authors.
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No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
aimsEmerging evidence supports artificial intelligence-enhanced electrocardiogram (AI-ECG) for detecting acute myocardial infarction (AMI), but real-world validation is needed. The aim of this study was to evaluate the performance of AI-ECG in detecting AMI in the emergency department (ED).
methodsThe Rule-Out acute Myocardial Infarction using Artificial intelligence Electrocardiogram analysis (ROMIAE) study is a prospective cohort study conducted in the Republic of Korea from March 2022 to October 2023, involving 18 university-level teaching hospitals. Adult patients presenting to the ED within 24 h of symptom onset concerning for AMI were assessed. Exposure included AI-ECG score, HEART score, GRACE 2.0 score, high-sensitivity troponin level, and Physician AMI score. The primary outcome was diagnosis of AMI during index admission, and the secondary outcome was 30 day major adverse cardiovascular event (MACE).
resultsThe study population comprised 8493 adults, of whom 1586 (18.6%) were diagnosed with AMI. The area under the receiver operating characteristic curve for AI-ECG was 0.878 (95% CI, 0.868-0.888), comparable with the HEART score (0.877; 95% CI, 0.869-0.886) and superior to the GRACE 2.0 score, high-sensitivity troponin level, and Physician AMI score. For predicting 30 day MACE, AI-ECG (area under the receiver operating characteristic, 0.866; 95% CI, 0.856-0.877) performed comparably with the HEART score (0.858; 95% CI, 0.848-0.868). The integration of the AI-ECG improved risk stratification and AMI discrimination, with a net reclassification improvement of 19.6% (95% CI, 17.38-21.89) and a C-index of 0.926 (95% CI, 0.919-0.933), compared with the HEART score alone.
conclusionsIn this multicentre prospective study, the AI-ECG demonstrated diagnostic accuracy and predictive power for AMI and 30 day MACE, which was similar to or better than that of traditional risk stratification methods and ED physicians.
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